mirror of
https://github.com/wassname/ray.git
synced 2026-07-01 14:19:38 +08:00
Eric Liang
60 lines
1.4 KiB
Python
60 lines
1.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import base64
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import numpy as np
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import ray
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_pinned_objects = []
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PINNED_OBJECT_PREFIX = "ray.tune.PinnedObject:"
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def pin_in_object_store(obj):
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"""Pin an object in the object store.
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It will be available as long as the pinning process is alive. The pinned
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object can be retrieved by calling get_pinned_object on the identifier
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returned by this call.
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"""
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obj_id = ray.put(_to_pinnable(obj))
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_pinned_objects.append(ray.get(obj_id))
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return "{}{}".format(PINNED_OBJECT_PREFIX,
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base64.b64encode(obj_id.id()).decode("utf-8"))
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def get_pinned_object(pinned_id):
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"""Retrieve a pinned object from the object store."""
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from ray.local_scheduler import ObjectID
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return _from_pinnable(
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ray.get(
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ObjectID(base64.b64decode(pinned_id[len(PINNED_OBJECT_PREFIX):]))))
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def _to_pinnable(obj):
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"""Converts obj to a form that can be pinned in object store memory.
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Currently only numpy arrays are pinned in memory, if you have a strong
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reference to the array value.
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"""
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return (obj, np.zeros(1))
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def _from_pinnable(obj):
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"""Retrieve from _to_pinnable format."""
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return obj[0]
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if __name__ == '__main__':
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ray.init()
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X = pin_in_object_store("hello")
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print(X)
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result = get_pinned_object(X)
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print(result)
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